Baltimore reached the lowest infant mortality rate the city has ever recorded in 2012. Denver Public School students saw test scores improve by 14% in reading and 23% in math. And between 2006 and 2012, low-income New Yorkers have accessed an additional $100 million in tax credits that they were previously leaving on the table.
These urban policy wins were not merely the products of creativity and inspiration. They were powered by cold, hard, data. Bridgespan, a nonprofit consultancy for philanthropists and mission-driven organizations, and the education organization America Achieves have released a big report packed with case studies that illuminate a broader trend: how data-driven decision making can lead to the most effective use of a city’s limited financial resources.
Take Baltimore. In 2009, the city launched an “outcomes budgeting” process. In a traditional city finance model, each department from Sanitation to Education gets its own budget line and fights for every item on it. There’s a built-in perverse incentive: Departments gain in size and importance when the problems they were set up to fight get worse. Instead, Baltimore funded a list of priorities like “better schools” and “safer streets.” They appointed “results teams” including insider officials, outside experts, and local residents to evaluate each outcome.
The city faces a $30 million budget shortfall this year, but thanks to this results-focused process, they’ve been able to make hard decisions the smart way. Rather than resorting to across-the-board cuts, they’ve been able to cut services that can’t demonstrate results, raise funding for highly effective programs, and even allocate money to an innovation fund.
“Traditional budgeting is easy, but it often produces budgets that protect underperforming services and punish services that deliver results and advance the city’s priorities,” Baltimore Mayor Stephanie Rawlings-Blake told Co.Exist. “In Baltimore, we turned that old model on its head by first seeking to better understand the results our residents desire and then building our budgets to achieve those outcomes. Thanks to outcome budgeting, we maintained and even enhanced funding for services that demonstrated effectiveness, even as we grappled with a virtually unprecedented fiscal crisis. I sincerely hope that this report will inspire more big cities–perhaps even the federal government–to consider outcome budgeting.”
The issues tackled by the projects in these pages range from truancy to poverty. But what they have in common is the theme of accountability and evidence-based policymaking. Just like the computer system Compstat led to a revolution in police work starting in New York City, and testing-based accountability measures have driven education reform nationwide, there is a strong case being made here that cities should invest in an infrastructure of evidence-gathering as a way of setting public priorities, picking winners and losers, and even convincing an often reluctant tax base to pay more money for programs that can be proven to work. That is the case even in a state as tax averse as Texas: In San Antonio, voters approved a 1/8‐cent sales tax increase to help fund public pre-K. One million of the program’s $28 million budget over eight years will go toward ongoing evaluation; only the centers that demonstrate results will stay open.
There is a big caveat to this trend of data-driven policymaking, and that involves deciding the standard of proof used to drive decisions. “City leaders should prioritize outcomes instead of just outputs,” the report cautions–that means multiple, meaningful, independent measures of success, not more easily trackable and manipulable single stats. Otherwise cities that rush into the “Geek City” category risk falling afoul of “When a measure becomes a target, it ceases to be a good measure.”